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Nonlinear identification of a gas turbine system in transient operation mode using neural network

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSNConference contribution/Paperpeer-review

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Nonlinear identification of a gas turbine system in transient operation mode using neural network. / Rahnama, M.; Ghorbani, H.; Montazeri, Allahyar.
Thermal Power Plants (CTPP), 2012 4th Conference on. IEEE, 2012. p. 1-6.

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSNConference contribution/Paperpeer-review

Harvard

Rahnama, M, Ghorbani, H & Montazeri, A 2012, Nonlinear identification of a gas turbine system in transient operation mode using neural network. in Thermal Power Plants (CTPP), 2012 4th Conference on. IEEE, pp. 1-6, 2012 4th Conference on Thermal Power Plants (CTPP), Tehran, Iran, Islamic Republic of, 18/12/12. <http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6486747>

APA

Vancouver

Rahnama M, Ghorbani H, Montazeri A. Nonlinear identification of a gas turbine system in transient operation mode using neural network. In Thermal Power Plants (CTPP), 2012 4th Conference on. IEEE. 2012. p. 1-6

Author

Rahnama, M. ; Ghorbani, H. ; Montazeri, Allahyar. / Nonlinear identification of a gas turbine system in transient operation mode using neural network. Thermal Power Plants (CTPP), 2012 4th Conference on. IEEE, 2012. pp. 1-6

Bibtex

@inproceedings{44a5748159e44b669b9b1af5f4439262,
title = "Nonlinear identification of a gas turbine system in transient operation mode using neural network",
abstract = "In this paper ANN (Artificial Neural Network) identification techniques are developed to estimate a General Electric frame 9, 116MW combined cycle, single shaft heavy duty gas turbine dynamic behaviors during loading process based on available operational data in Montazer Ghaem power plant in Karaj. Related Input and output data are chosen based on thermodynamics and first order linear models. Electrical power and exhaust gas temperature are chosen as system main outputs which can be expressed by fuel flow, shaft speed and compressor inlet guide vanes considering the ambient temperature effects. The operating condition of the gas turbine during identification procedure is considered from full speed no load to full load. Comprehensive results perform that this model outputs is closer to the experimental data than conventional NARX models and can predict system behaviors perfectly.",
author = "M. Rahnama and H. Ghorbani and Allahyar Montazeri",
year = "2012",
language = "English",
isbn = "978-1-4673-4844-7",
pages = "1--6",
booktitle = "Thermal Power Plants (CTPP), 2012 4th Conference on",
publisher = "IEEE",
note = "2012 4th Conference on Thermal Power Plants (CTPP) ; Conference date: 18-12-2012 Through 19-12-2012",

}

RIS

TY - GEN

T1 - Nonlinear identification of a gas turbine system in transient operation mode using neural network

AU - Rahnama, M.

AU - Ghorbani, H.

AU - Montazeri, Allahyar

PY - 2012

Y1 - 2012

N2 - In this paper ANN (Artificial Neural Network) identification techniques are developed to estimate a General Electric frame 9, 116MW combined cycle, single shaft heavy duty gas turbine dynamic behaviors during loading process based on available operational data in Montazer Ghaem power plant in Karaj. Related Input and output data are chosen based on thermodynamics and first order linear models. Electrical power and exhaust gas temperature are chosen as system main outputs which can be expressed by fuel flow, shaft speed and compressor inlet guide vanes considering the ambient temperature effects. The operating condition of the gas turbine during identification procedure is considered from full speed no load to full load. Comprehensive results perform that this model outputs is closer to the experimental data than conventional NARX models and can predict system behaviors perfectly.

AB - In this paper ANN (Artificial Neural Network) identification techniques are developed to estimate a General Electric frame 9, 116MW combined cycle, single shaft heavy duty gas turbine dynamic behaviors during loading process based on available operational data in Montazer Ghaem power plant in Karaj. Related Input and output data are chosen based on thermodynamics and first order linear models. Electrical power and exhaust gas temperature are chosen as system main outputs which can be expressed by fuel flow, shaft speed and compressor inlet guide vanes considering the ambient temperature effects. The operating condition of the gas turbine during identification procedure is considered from full speed no load to full load. Comprehensive results perform that this model outputs is closer to the experimental data than conventional NARX models and can predict system behaviors perfectly.

M3 - Conference contribution/Paper

SN - 978-1-4673-4844-7

SP - 1

EP - 6

BT - Thermal Power Plants (CTPP), 2012 4th Conference on

PB - IEEE

T2 - 2012 4th Conference on Thermal Power Plants (CTPP)

Y2 - 18 December 2012 through 19 December 2012

ER -